Prentice Bisbal wrote:
> Vincent Diepeveen wrote:
>> Running 128 parallel sessions of md5sum is not so interesting at all, we
>> all believe this can be done fast.
>>>> Vincent,
>> That is the whole point of my original posting. The point was NEVER to
> demonstrate the use of GPUs for streaming MD5-encrypted data. This was
> the point of my posting:
>> 1. To prove that CUDA programming is NOT as difficult as you made it out
> to be.
Hi Prentis:
There is a general impression that CUDA is hard. I am not sure
precisely where this is coming from, but this is what I am hearing from
multiple quarters. Usually from people whom have not tried it.
>> 2. To demonstrate the performance improvement you can get by
> parallelizing an operation using CUDA. The MD5 algorithm was perfect for
> this. No claims were ever made as to the need for parallelizing MD5.
> There is value, however, if your goal is to recover (discover?) an
> MD5-hashed password through a brute-force attack. Last time I checked,
> MD5 password s are the default for most Linux distros.
>> 3. To show that more than just "hobbyists" are investigating GPUs.
I think I can comment on some papers submitted to various
conferences. I am privy to some work not yet published, so I can't
recount that. In short, we have seen papers on segmentation of medical
image data sets (Liver segmentation to be precise) on CUDA platforms,
getting ~70x performance over a single machine. I am aware of some
unnamed bioinformatics applications seeing ... nice ... speedups on
CUDA. None of these are hobbyist things. The CUDA eco-system is
growing rapidly, with real users.
We have 3 CUDA machines in house, one of them my laptop :). I just
need to get on a few planes so I can spend that time coding ...
--
Joseph Landman, Ph.D
Founder and CEO
Scalable Informatics LLC,
email: landman at scalableinformatics.com
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